|
|
Absolute deviation, 绝对离差
: G& r/ Q( N& l. S xAbsolute number, 绝对数( S7 b2 t C8 d( I G2 n
Absolute residuals, 绝对残差
6 o$ @3 [3 g: ^9 {( Z {+ n9 ~Acceleration array, 加速度立体阵4 T/ f0 E! k; y; ^- B5 H5 e
Acceleration in an arbitrary direction, 任意方向上的加速度! ^3 O7 }$ j0 ^9 [5 x( l
Acceleration normal, 法向加速度
' L8 p, p9 l+ b0 \4 o* sAcceleration space dimension, 加速度空间的维数' [7 y! [5 u# ?
Acceleration tangential, 切向加速度+ P& N8 `8 ]& Z$ ]6 `& S
Acceleration vector, 加速度向量
( F' d0 J3 p" u- A- b7 ?+ VAcceptable hypothesis, 可接受假设
, x* o o3 x. k) i7 r3 rAccumulation, 累积
; ^! F3 r) t5 g D* t/ p) {, X3 UAccuracy, 准确度. _. f1 l. A4 i3 O) F' X0 c0 i4 k* W
Actual frequency, 实际频数) @( G" R. Y2 t: N" {
Adaptive estimator, 自适应估计量9 [) D: y, f2 ?& N/ ]6 \; H( K z
Addition, 相加+ W4 I3 k1 u7 e) N
Addition theorem, 加法定理
0 t4 A* O, X8 x1 ]. y6 v4 kAdditivity, 可加性
+ Z4 |! p, `( B$ XAdjusted rate, 调整率
+ M1 I/ q3 j5 D3 e; t! S) rAdjusted value, 校正值
$ \! \% C2 V5 GAdmissible error, 容许误差3 ?" [* p# L2 @+ a( G3 K" m i4 [
Aggregation, 聚集性
P4 ~9 }( z( Y$ `# G9 p2 h9 e5 q/ f$ t7 ~Alternative hypothesis, 备择假设8 }' O) D$ u3 c1 ~5 U4 m. K% [4 f
Among groups, 组间
4 T* @1 j3 V/ n/ N. lAmounts, 总量
1 J4 f9 e! e* w, `Analysis of correlation, 相关分析. S) ^* \5 f: ~: V" ^! J9 F
Analysis of covariance, 协方差分析
5 }4 s, h4 X6 ^" gAnalysis of regression, 回归分析) O5 l9 n4 E, c/ x1 n
Analysis of time series, 时间序列分析+ _5 T! c% p2 K+ k2 ^
Analysis of variance, 方差分析
/ m6 r! L3 s; ~9 Y9 e/ ?+ J2 l5 CAngular transformation, 角转换- e$ o0 Z, s: J, }( S% h {
ANOVA (analysis of variance), 方差分析
1 u; s5 ?3 t3 }" U6 e( eANOVA Models, 方差分析模型8 p; [+ z* e7 [% X, J( J% A; ^# b
Arcing, 弧/弧旋) T; I- u( n6 N/ x. g9 Q
Arcsine transformation, 反正弦变换
6 m9 t p2 ^# v$ |+ H2 OArea under the curve, 曲线面积
) I) f2 I K3 b6 V2 m! _AREG , 评估从一个时间点到下一个时间点回归相关时的误差 - }2 G4 i8 \0 `
ARIMA, 季节和非季节性单变量模型的极大似然估计 8 k0 E8 ^& Q% c/ | F
Arithmetic grid paper, 算术格纸
. |6 L6 P7 h2 L% C/ ~: RArithmetic mean, 算术平均数
1 b3 `+ f; P" Z, F; mArrhenius relation, 艾恩尼斯关系: j2 Z9 m3 H) p" G2 U0 @# Y
Assessing fit, 拟合的评估! R% K" J9 F0 I% [5 t
Associative laws, 结合律8 n# |: Y& n6 f1 s
Asymmetric distribution, 非对称分布
' z( h4 l4 g" A/ ]& m+ UAsymptotic bias, 渐近偏倚
& O$ R# w' [' f- q. uAsymptotic efficiency, 渐近效率# M) Z) q2 K5 L. e6 r* ~ w
Asymptotic variance, 渐近方差8 S1 l6 I1 X, b5 j3 f
Attributable risk, 归因危险度9 e: U, x( H) o) _( d
Attribute data, 属性资料
& C( N! u7 j9 I) n& XAttribution, 属性
* N( o2 O# R+ E' ?: ^! FAutocorrelation, 自相关
) S; @- ^( G" r0 lAutocorrelation of residuals, 残差的自相关
0 ~$ h4 W7 h1 w. g, Q6 `Average, 平均数8 Z3 p8 [. ], s8 j4 w/ q t: k
Average confidence interval length, 平均置信区间长度0 x8 V% M. h& _0 V9 Z! O
Average growth rate, 平均增长率
- r' C4 a. V! yBar chart, 条形图2 `& Z2 ^8 U: [5 F/ r+ n7 b9 M
Bar graph, 条形图% e, c8 k9 k: A/ W2 w) a; F# V
Base period, 基期
; ]" _2 Y4 q* HBayes' theorem , Bayes定理1 j, u) e: T5 e/ h$ ?
Bell-shaped curve, 钟形曲线# F% x q* f% B/ v" {9 e; ~
Bernoulli distribution, 伯努力分布
* z5 z8 Q5 Q+ Q' s! l" u& w1 }Best-trim estimator, 最好切尾估计量4 ^$ D0 z N( l# ?, K& y% I
Bias, 偏性0 W0 E8 k- G3 d
Binary logistic regression, 二元逻辑斯蒂回归; V" K s+ k/ {5 p
Binomial distribution, 二项分布
9 D8 v" ]7 d) PBisquare, 双平方+ r6 [* j' Z1 M8 S
Bivariate Correlate, 二变量相关+ \! Q& J: t ?( G2 p1 O
Bivariate normal distribution, 双变量正态分布' i% g# i. Y2 [8 r' v/ N1 c% }
Bivariate normal population, 双变量正态总体
0 p, j6 a2 h* X& z1 G, XBiweight interval, 双权区间; p! r- s2 n3 a1 v2 }
Biweight M-estimator, 双权M估计量
7 C, t2 P0 D3 j5 B0 PBlock, 区组/配伍组! V7 J$ O8 j+ _4 f
BMDP(Biomedical computer programs), BMDP统计软件包/ \* i" s) b4 \% I
Boxplots, 箱线图/箱尾图
: p% J7 C: w3 t% _* |Breakdown bound, 崩溃界/崩溃点
0 T5 l0 m9 W+ c: m! v) ]( L6 \% l; xCanonical correlation, 典型相关* E0 P/ k' z3 V9 M( R3 V- w
Caption, 纵标目
" r! f% N+ L' u/ h# QCase-control study, 病例对照研究: J/ u( I! c0 ]" F
Categorical variable, 分类变量( I4 Y0 D) b+ |2 l
Catenary, 悬链线3 m9 @0 h* J- W' ~2 |6 D& J
Cauchy distribution, 柯西分布
8 s7 _0 W5 q4 ?* WCause-and-effect relationship, 因果关系0 t, h6 s/ R8 J4 w, D6 Z
Cell, 单元: ~2 T- ^" H) y; [! Z6 A! q& k
Censoring, 终检4 Q9 I9 n) L1 [& f" K9 y: h
Center of symmetry, 对称中心
# Q' P+ y0 `5 r, r* VCentering and scaling, 中心化和定标& k% B4 Z7 e, T, y; T
Central tendency, 集中趋势" ^( a2 ~! N* n% E; X1 ^% A6 E
Central value, 中心值
R, P2 C8 [% Y, C5 X2 L- QCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测8 T1 o5 G$ R1 b- |. u. O
Chance, 机遇
" W7 u) \8 V5 f4 Q+ nChance error, 随机误差( I+ i$ o: f+ m; Z2 _: p& Z. ~2 x; H
Chance variable, 随机变量. p3 u4 _0 S) \8 O
Characteristic equation, 特征方程
, [3 o5 [- }! {# ]9 l/ PCharacteristic root, 特征根. d8 b1 G' M( \. y$ O" j
Characteristic vector, 特征向量: y* q7 M4 D8 j' y
Chebshev criterion of fit, 拟合的切比雪夫准则! [0 y1 ?! c; J" W2 K/ f0 V; p
Chernoff faces, 切尔诺夫脸谱图
4 @; A! ?6 J, m! R, C/ y& tChi-square test, 卡方检验/χ2检验
( E" b: m5 v1 Q/ p! ]Choleskey decomposition, 乔洛斯基分解# z4 R6 \/ t+ q/ z. x
Circle chart, 圆图 9 l+ b' p! R4 j% }3 q& C2 ~6 a5 {
Class interval, 组距
; ~2 H6 ^2 Q$ E4 A4 d: c- D; X- fClass mid-value, 组中值' }6 C% |0 @" Y/ z6 B; V1 O2 k
Class upper limit, 组上限
& w. y2 I6 B6 ?! q0 U( ?Classified variable, 分类变量
: ?% Z! a# K; f. G/ v) y' ~# `Cluster analysis, 聚类分析
0 |# r1 \! w3 K, f: P& W7 QCluster sampling, 整群抽样
; f$ h+ f5 q( L. g5 O$ rCode, 代码
( W+ x% W5 I8 g8 T1 r. }0 |/ DCoded data, 编码数据/ ?/ y8 T& H3 y6 Y! C, Z
Coding, 编码
9 O& j. X5 F" k5 [ O2 H) T, UCoefficient of contingency, 列联系数1 m/ y" R* o0 _) A/ ^9 _9 J0 x$ y
Coefficient of determination, 决定系数/ j3 N1 ~5 d- ?, m/ u; _
Coefficient of multiple correlation, 多重相关系数7 m) c# _3 J1 i! I3 @ v
Coefficient of partial correlation, 偏相关系数% G+ m/ N2 w. N, U5 M* W) b! c/ u+ D
Coefficient of production-moment correlation, 积差相关系数& p& G4 M {, Z7 f
Coefficient of rank correlation, 等级相关系数
/ [8 B& Z* {# f# Q( a0 a7 CCoefficient of regression, 回归系数0 K- g7 r2 S1 p% @2 b
Coefficient of skewness, 偏度系数7 R. D; ^( u; ]$ V
Coefficient of variation, 变异系数+ x/ `2 j2 A; J: n
Cohort study, 队列研究
# e$ L& ~) [3 q4 @( CColumn, 列
3 d5 o0 c5 I& ] C# | S: HColumn effect, 列效应
. W" j4 o4 O% eColumn factor, 列因素+ C3 H+ H# w, W$ T$ R, @7 k; j
Combination pool, 合并
9 B& \9 e& R. K7 G6 G! J# MCombinative table, 组合表
9 D* g7 C9 P N1 w0 { A ]) t4 ZCommon factor, 共性因子( v0 X5 B: y) K1 |, D8 J
Common regression coefficient, 公共回归系数
# }% j" B% A, b; Q& p4 vCommon value, 共同值
3 s( X0 d9 d* P5 _% V; O* N0 Y& OCommon variance, 公共方差
$ C& H3 h% b$ C7 E1 x+ UCommon variation, 公共变异6 Q1 t0 H; k7 O, d
Communality variance, 共性方差1 a! b8 H& A' z. i6 F2 [. {5 b g
Comparability, 可比性# |' s7 n$ r% H; L
Comparison of bathes, 批比较$ I4 J: a, E f) c
Comparison value, 比较值
- ~" C/ ~- j& D2 E. r- w/ GCompartment model, 分部模型5 h+ v- q# Q$ C) m: w* `
Compassion, 伸缩2 h% K2 ^% S* o+ {" G+ _# n3 D1 I7 o
Complement of an event, 补事件
3 _( `" l7 M aComplete association, 完全正相关
% U/ \& K) I$ v E! `" g9 dComplete dissociation, 完全不相关
[5 d: D, W/ y" I0 nComplete statistics, 完备统计量+ ^! K) D+ ~( L4 q" S. K6 }: \) \
Completely randomized design, 完全随机化设计6 u# g8 P. S# g1 v6 l4 u1 X7 h$ @
Composite event, 联合事件
7 i* ~/ g* u" v) EComposite events, 复合事件- i+ A' T" l# O) t1 e
Concavity, 凹性, H- J, m0 q/ {5 c
Conditional expectation, 条件期望; p" @9 m( Q2 a
Conditional likelihood, 条件似然' ~0 {5 C$ n8 C6 }
Conditional probability, 条件概率
& A! a' x I5 v6 IConditionally linear, 依条件线性% Q% M+ E5 N/ S% c! B8 Z
Confidence interval, 置信区间! `; Q% H7 I8 o0 @5 Y5 D2 f/ k
Confidence limit, 置信限
2 T) J: x2 f! X! U5 nConfidence lower limit, 置信下限
- K& O( K# ?# B$ @; DConfidence upper limit, 置信上限
% d! s5 w8 G* X2 g) ~% C" GConfirmatory Factor Analysis , 验证性因子分析
; f, s3 \+ c8 ^5 n/ c5 l7 vConfirmatory research, 证实性实验研究
8 u4 m1 ]; H1 D* N8 v6 @Confounding factor, 混杂因素1 v z& W! Y: M% c( U
Conjoint, 联合分析9 d) Z3 Z/ C6 a5 b2 M
Consistency, 相合性2 v% ^9 a4 O: D" F7 R. s
Consistency check, 一致性检验
2 @1 c8 L Y% o& }6 w& `* v1 p( R+ mConsistent asymptotically normal estimate, 相合渐近正态估计. X( {* e- g$ w9 C
Consistent estimate, 相合估计
2 n) [1 O; p, I9 xConstrained nonlinear regression, 受约束非线性回归
8 P+ g5 I1 I4 O; r! _Constraint, 约束
1 _- u0 ]# d+ `# ~3 @' F1 yContaminated distribution, 污染分布: ^. J9 F- x( h) x& P; { W! y
Contaminated Gausssian, 污染高斯分布5 C1 I4 f) {! K. }0 v
Contaminated normal distribution, 污染正态分布& _' G7 U0 W; ]; S e; q% X) g: E
Contamination, 污染4 ?/ \( s, v+ N7 Z' f; S
Contamination model, 污染模型
1 n) o' J) T3 s: L5 dContingency table, 列联表
" t m9 s5 c/ v" RContour, 边界线
! K5 e8 \$ _7 {/ G- ~* \Contribution rate, 贡献率
6 [" ~0 S+ x( S: D4 M' ]Control, 对照
1 n7 u. N7 p" N* r* p1 Y! vControlled experiments, 对照实验
) V! ^% z3 q( r) X# Y' O' S* oConventional depth, 常规深度# P# h k% u6 u! @
Convolution, 卷积) K6 s+ i; U0 Q$ w3 ^% L
Corrected factor, 校正因子2 G @6 g5 Q. }6 @8 C! R
Corrected mean, 校正均值
! l6 S" G# E* y0 O# X4 B& @: Q; |Correction coefficient, 校正系数
/ m' i0 e0 g; Q4 D3 UCorrectness, 正确性4 h: s4 G5 V; h2 g) s
Correlation coefficient, 相关系数7 S1 h- T o8 [+ d
Correlation index, 相关指数
j1 P i, J9 r# k3 r$ \6 e7 }! ]Correspondence, 对应3 R9 k2 G( n7 Y& ~# n
Counting, 计数
9 g# R0 b! [, G" L( i" _' TCounts, 计数/频数0 J% g( A. B% r M
Covariance, 协方差; l6 N# Z* e9 ~5 A0 ~
Covariant, 共变 - j/ F& i( d5 L0 p, f
Cox Regression, Cox回归
. \3 \7 _: l4 Q; i5 x2 ACriteria for fitting, 拟合准则
7 B! Y/ t; N2 g: s4 R# jCriteria of least squares, 最小二乘准则
: _: ?7 F) h( B" b" XCritical ratio, 临界比
" y0 O9 y# j0 N& P4 u( e' CCritical region, 拒绝域
1 N; I: Q% K# }/ A# ~Critical value, 临界值
) ^7 ]' Q' F0 L" L+ j: T' d# ]& OCross-over design, 交叉设计
% E; d9 I7 i2 D/ w( ^# ACross-section analysis, 横断面分析! Y: r$ k( ` |* A
Cross-section survey, 横断面调查
' x ?: O! {/ N' Z% o9 m1 R3 k3 m8 @' XCrosstabs , 交叉表 8 z4 y1 K- o8 P5 Z9 b& u% l6 q' K( ]
Cross-tabulation table, 复合表4 i; F7 q7 h: H3 v# u
Cube root, 立方根; u ?# U+ z4 k1 p# K& U
Cumulative distribution function, 分布函数
& C* F c6 N G- T8 kCumulative probability, 累计概率0 I5 B# E( {5 ~# W* `% E( {
Curvature, 曲率/弯曲, |. X3 T- n1 C3 e+ }; T
Curvature, 曲率( y; ~: y# L5 T, I8 a
Curve fit , 曲线拟和
0 ^! _: K K( s: A( SCurve fitting, 曲线拟合
* o: y- \8 W' pCurvilinear regression, 曲线回归- r( ^8 A8 q/ f# ~* m
Curvilinear relation, 曲线关系
. C" r" S# \7 ^9 a" x6 VCut-and-try method, 尝试法0 Y2 ?; V' G/ `1 {- t# m
Cycle, 周期. F- D' I* H; w1 w5 G8 H8 ~
Cyclist, 周期性+ O7 \4 U' {6 K2 z6 N6 A& D
D test, D检验
B: X i1 E L% g1 w. GData acquisition, 资料收集0 S! K3 z& U& V. ^- O" o. _; s
Data bank, 数据库
, N9 Q/ K- p5 f, bData capacity, 数据容量9 P1 g5 ^, d# p9 V: ~& G8 T
Data deficiencies, 数据缺乏
4 G' p5 a5 R4 i& q0 |9 M" eData handling, 数据处理( T) |% U. E" e& ]7 G* `4 x
Data manipulation, 数据处理& w* f' ?# Q, D) H& a, {
Data processing, 数据处理: E' u# a1 k. f# N1 `
Data reduction, 数据缩减
: p9 W9 q9 \+ P$ g' SData set, 数据集
; X6 Z: n$ C) H& b( g! aData sources, 数据来源
5 c' V3 i+ e6 s- }Data transformation, 数据变换
: i" A+ N4 U/ `: f2 I% P) K$ SData validity, 数据有效性! P+ L6 [+ _/ Q- [' A; t6 v0 B
Data-in, 数据输入6 l( r8 P* i; N1 A4 T M6 D
Data-out, 数据输出
$ g) l7 W7 ^/ t8 ODead time, 停滞期
! h( p. Q8 @2 o0 D. c* t& XDegree of freedom, 自由度9 L k9 Z) t* X& S H% {6 ^6 [; p) N
Degree of precision, 精密度0 e% A2 K/ ], z' ?
Degree of reliability, 可靠性程度' N4 `, \8 _9 K
Degression, 递减
. T6 K* o/ n2 e- B/ DDensity function, 密度函数
! Y% a3 x, @2 \7 U3 IDensity of data points, 数据点的密度5 s7 Y* ^2 H) A+ q7 r4 x g' L( ^
Dependent variable, 应变量/依变量/因变量4 ]+ m* T: E5 e8 V4 f8 D
Dependent variable, 因变量) C6 L* H: f& m& W, _
Depth, 深度
& ]. ]. I2 p/ Y& @ W' q z2 XDerivative matrix, 导数矩阵
# p; G1 q5 x) c6 M' } |Derivative-free methods, 无导数方法4 c9 R: D, C8 h1 b9 T
Design, 设计% R& c3 F' U# o' e; l9 R3 T
Determinacy, 确定性6 n3 Q# u3 P2 G! a$ ]) D: ^
Determinant, 行列式8 C# X( X' ]& } O# X4 C" B
Determinant, 决定因素4 O7 L. i3 W; A0 \2 P
Deviation, 离差& a) y4 H _# U5 N1 T' f9 M
Deviation from average, 离均差
; G$ t2 u3 v+ w; b0 e/ e! }Diagnostic plot, 诊断图
7 b5 V9 z1 U6 A$ ^9 SDichotomous variable, 二分变量 T4 x4 w; j% }7 k2 T
Differential equation, 微分方程; m; q5 z/ ^6 p( U! S5 M6 _
Direct standardization, 直接标准化法
: z2 s: X; O8 e* l8 q* CDiscrete variable, 离散型变量, \3 s- s+ g1 U! D0 T: ~* ~0 B% O
DISCRIMINANT, 判断 9 V6 m# x+ o) b
Discriminant analysis, 判别分析: l; i' e# t4 j. Z! J' e$ W
Discriminant coefficient, 判别系数
2 e2 j2 n# G* r# UDiscriminant function, 判别值2 s. e- n% f3 s
Dispersion, 散布/分散度
1 C: g D7 y" N8 k- _Disproportional, 不成比例的- I, _! Q" A4 M- Q. Q
Disproportionate sub-class numbers, 不成比例次级组含量
4 a) L! u) t4 R7 F4 E6 TDistribution free, 分布无关性/免分布
) ~9 b% Y4 \2 i% }7 e# ?Distribution shape, 分布形状
. w/ J, k, x* K1 qDistribution-free method, 任意分布法
( L3 v' X4 \& a3 L4 S7 h! _Distributive laws, 分配律
2 O7 L B" L& k( D9 N( {* g! o: ZDisturbance, 随机扰动项# t3 F8 ~* g9 @ k T
Dose response curve, 剂量反应曲线 M: ^/ z; G# F
Double blind method, 双盲法 G( v" u0 [5 Q' v
Double blind trial, 双盲试验$ Z* z8 i* q0 K
Double exponential distribution, 双指数分布+ |$ R- [1 h+ H
Double logarithmic, 双对数! I, p/ I) d8 ^/ l# v
Downward rank, 降秩, ^7 \& S/ d! I1 f; u% l& d/ i) J, p
Dual-space plot, 对偶空间图
/ c. f" t" c; z6 X2 @9 j: u, PDUD, 无导数方法
2 J3 C, \0 E0 A- oDuncan's new multiple range method, 新复极差法/Duncan新法
- Y( S' g7 z, yEffect, 实验效应" Y) C4 r) ?) r6 d/ X2 L: O6 r
Eigenvalue, 特征值/ i8 o+ Y" l( _$ [
Eigenvector, 特征向量% v9 P+ x m/ B4 _, j
Ellipse, 椭圆" I9 D' z8 @+ f! b: p) p& [
Empirical distribution, 经验分布
1 H- [7 V6 M3 dEmpirical probability, 经验概率单位. \% c6 |' }+ U+ U$ O, G T" a
Enumeration data, 计数资料5 C' _3 D/ u% C/ d+ U& N( W. J3 u
Equal sun-class number, 相等次级组含量, d& P0 |+ g0 \$ T
Equally likely, 等可能
0 M; R' Q6 I2 L: Y2 p& [: yEquivariance, 同变性2 K) L. A' z# f! I' j/ P
Error, 误差/错误! ?% T# U1 h4 g; e8 e& a
Error of estimate, 估计误差
# a. N& U. j) z/ @7 u8 g2 ^: n' Z( y% kError type I, 第一类错误" v2 x$ ]# P( g2 }. m3 W
Error type II, 第二类错误
# S: \, W3 C8 U! L5 V* iEstimand, 被估量
3 f2 \6 F: B6 o! fEstimated error mean squares, 估计误差均方
' T0 j2 ?2 G- n) B; y6 `0 H. H/ iEstimated error sum of squares, 估计误差平方和! S7 l: m: y2 _
Euclidean distance, 欧式距离0 |# A/ {" f# z) g9 H
Event, 事件1 g B6 R* Y2 O* b1 J% z& y0 e
Event, 事件
5 K3 @. o0 t1 w" `6 V3 @: YExceptional data point, 异常数据点6 g/ [, U. M3 x1 ~+ _4 f7 ?1 p4 _( f: A
Expectation plane, 期望平面
. |7 a4 U# A5 a7 e) hExpectation surface, 期望曲面- W/ k- b8 F5 i# ]
Expected values, 期望值
( ~+ u) O( S/ QExperiment, 实验
) A' b$ b- K% K2 o$ g, ` z/ vExperimental sampling, 试验抽样
' h5 x# ~' m( Q' _0 K, S( ~+ MExperimental unit, 试验单位
* a+ Y' `6 \& i* |Explanatory variable, 说明变量& s$ x3 {" i- I# c- P
Exploratory data analysis, 探索性数据分析5 N2 M8 z5 j6 D" n& ~# y5 S) U
Explore Summarize, 探索-摘要
! C9 w+ `& Z5 m8 q+ p. l6 d/ Z; m% n/ pExponential curve, 指数曲线
7 s5 \5 R$ P. a; Z( N1 E8 O( P( m4 u! eExponential growth, 指数式增长
$ v+ V2 p9 z' aEXSMOOTH, 指数平滑方法
( ]' j$ x; ^6 x: C$ FExtended fit, 扩充拟合: F9 }2 b! l5 Y( z0 I$ ^# j
Extra parameter, 附加参数
' K+ i+ E8 E9 jExtrapolation, 外推法* `' ^; w" Q' o4 c+ x3 K* r0 B/ A
Extreme observation, 末端观测值+ ?# @1 C% K0 v3 p3 B# t: }
Extremes, 极端值/极值4 N! M* F$ ?' |% P
F distribution, F分布9 P% G- ~- S* V$ x- r6 Y4 j/ l
F test, F检验) F, E5 t- Z1 t" ^% S6 C
Factor, 因素/因子. N: H1 @" a! B! v/ F
Factor analysis, 因子分析( W, O( o F5 [, m6 P: y8 E! n
Factor Analysis, 因子分析
+ H* j9 D0 R9 FFactor score, 因子得分 3 o" t% Z/ {# Y, N
Factorial, 阶乘* n$ y& m9 K7 F3 q; J
Factorial design, 析因试验设计: u7 I" a/ f- ~/ L
False negative, 假阴性
0 z1 }' M! W+ p% G/ G9 A9 jFalse negative error, 假阴性错误
) C& X) T+ v% VFamily of distributions, 分布族
5 W8 o) b4 j6 F: ^Family of estimators, 估计量族
$ f9 P) |8 b. k% S: FFanning, 扇面
5 ^# c; ?/ S& e7 zFatality rate, 病死率% v( I) ~6 i7 r& j- n7 u1 M( V
Field investigation, 现场调查
& m. }( V" Y5 s( tField survey, 现场调查! A$ a1 }* O: b; W7 c
Finite population, 有限总体
( Y6 `+ g! Y1 QFinite-sample, 有限样本
! Y, E( N4 Q- D' ?First derivative, 一阶导数
0 {) s S, ?" S8 `8 @0 G3 `8 K8 ^First principal component, 第一主成分
" `* i" t$ ]+ _3 n8 ^( pFirst quartile, 第一四分位数
* Y* O4 X6 ?% d- K- \3 ]Fisher information, 费雪信息量
% E/ R/ Y- b* ?/ kFitted value, 拟合值
% V& S' D4 U+ hFitting a curve, 曲线拟合
5 a5 Y' r+ X4 b/ t% A" x. S& ~Fixed base, 定基
- l) ^: }5 J4 O& s* P3 T* L1 k) EFluctuation, 随机起伏0 ^7 l0 `" s8 Q6 M6 z* X
Forecast, 预测8 }! o) k4 O7 Z& d; ?
Four fold table, 四格表
! H8 W. P! W2 z' bFourth, 四分点
* `* Y; u) s% i5 e/ VFraction blow, 左侧比率
; c0 T& }! A8 jFractional error, 相对误差
& c0 H6 O1 M+ X& ?) @! |, W* aFrequency, 频率
2 n/ p3 @5 O% G4 [5 qFrequency polygon, 频数多边图
: f2 M: J5 m8 D" w$ MFrontier point, 界限点0 T+ h: G. F3 X7 p/ L3 n
Function relationship, 泛函关系
0 W- \# t/ q+ Q$ k" nGamma distribution, 伽玛分布) P: V) [( f) }
Gauss increment, 高斯增量
6 \6 x5 X! e8 A, Q+ |0 n" m6 WGaussian distribution, 高斯分布/正态分布9 C& z' J u: |- W6 P. |$ p
Gauss-Newton increment, 高斯-牛顿增量
! _' p* E) R1 @General census, 全面普查
' ?" p- |' @ O' e( w) U+ L9 gGENLOG (Generalized liner models), 广义线性模型
/ x9 X1 [' {1 g5 \, R5 kGeometric mean, 几何平均数1 [# O# D, V: }9 U9 s# o
Gini's mean difference, 基尼均差
5 y/ V) \; |9 u5 Z/ bGLM (General liner models), 一般线性模型
9 J0 e- T i/ x0 T: IGoodness of fit, 拟和优度/配合度
9 i; Z& c; Q- v/ l" J' y8 iGradient of determinant, 行列式的梯度
9 ^3 L8 K3 N6 i% P' j' yGraeco-Latin square, 希腊拉丁方
% y$ `1 P) i! NGrand mean, 总均值& c1 O3 \, n; |% N) e j2 `
Gross errors, 重大错误$ r# ^: z* Z/ Z0 H
Gross-error sensitivity, 大错敏感度. d" c1 f( ]7 w; _
Group averages, 分组平均! R$ }) F* v: F" }* { a4 L
Grouped data, 分组资料, n, m' p1 P0 \; D2 N
Guessed mean, 假定平均数2 D$ J( ?' a, ?' p9 }
Half-life, 半衰期
6 c" E; O2 ~2 t t+ n x# NHampel M-estimators, 汉佩尔M估计量' N; j, F8 r! n* o
Happenstance, 偶然事件
4 I2 O: E5 m0 R: VHarmonic mean, 调和均数( s' G% L" R3 k" h. p) }! Y5 l
Hazard function, 风险均数 y4 F7 B' x+ m* P4 }
Hazard rate, 风险率0 j. |8 G2 s. V6 {4 X* H6 y3 J
Heading, 标目 5 ?4 ~# q" U7 e
Heavy-tailed distribution, 重尾分布
5 ^. h4 A% q; O- wHessian array, 海森立体阵
; \& {; {- o) x: c7 F/ ^1 U# v2 FHeterogeneity, 不同质7 a) L( m) Q, ?# `
Heterogeneity of variance, 方差不齐 3 b6 B$ I! H Z" ~; n7 V
Hierarchical classification, 组内分组
2 m& B$ G. V- s y- l6 i, M% KHierarchical clustering method, 系统聚类法
! v) y% t. o. aHigh-leverage point, 高杠杆率点
+ Z) e( g1 |- t+ C! qHILOGLINEAR, 多维列联表的层次对数线性模型; h' s ?+ v) E" @( Z: v y7 g! j
Hinge, 折叶点- k$ R, a* @7 ?/ ?5 K
Histogram, 直方图
% j1 V; ]1 b, ]Historical cohort study, 历史性队列研究 ' n( z- b( Y: r) A; c4 [$ r
Holes, 空洞* u! a) F) O" R1 N2 y
HOMALS, 多重响应分析# P; Q% X9 u& X$ e
Homogeneity of variance, 方差齐性
/ [# Q/ K* y2 Z6 gHomogeneity test, 齐性检验% b& {+ W) n* y+ P& o! I) c( L
Huber M-estimators, 休伯M估计量
' K! @- T# b+ {+ D" N8 e3 r3 CHyperbola, 双曲线 s8 W0 ]0 _$ q+ I
Hypothesis testing, 假设检验
- k7 O2 r0 t! a+ w% I5 ^Hypothetical universe, 假设总体
8 h$ w) j' e0 `# wImpossible event, 不可能事件6 F8 c5 N# v/ l6 G
Independence, 独立性
0 s4 o5 Z3 x$ d: a; G+ lIndependent variable, 自变量
; i! x, I7 `' t& uIndex, 指标/指数
1 u2 U$ t, {& UIndirect standardization, 间接标准化法& K( P0 X) _+ ^9 u% \
Individual, 个体+ e' A$ S% i; ^5 q& P. s
Inference band, 推断带& T6 _# [4 T, ?, E2 Q3 k3 \
Infinite population, 无限总体
5 Z$ o- W0 d& n+ }0 |Infinitely great, 无穷大
+ M7 S+ g% b: d* x4 b5 GInfinitely small, 无穷小
8 G- `. n6 c ~Influence curve, 影响曲线) h$ J# k0 [1 }* q
Information capacity, 信息容量3 `) O( M ?" ]# g8 D4 l8 U
Initial condition, 初始条件+ G; a) s& g5 x- S/ }6 c
Initial estimate, 初始估计值7 f1 G! F5 t! \- z- C6 V1 Y! v
Initial level, 最初水平! ]0 _: V; x& a- l! A
Interaction, 交互作用+ c+ n4 z' c: k: I
Interaction terms, 交互作用项
7 ?+ L! J5 X0 p% o) ^Intercept, 截距" ?! w( a/ i! I8 F- T8 |
Interpolation, 内插法
. P/ d0 W" h( O) ?9 \7 u3 xInterquartile range, 四分位距& q) x- O% h8 a0 A/ R
Interval estimation, 区间估计6 K, W% b2 B$ z2 ^6 H! `" M+ \1 f/ j
Intervals of equal probability, 等概率区间
: d( B+ ^/ w; aIntrinsic curvature, 固有曲率
. x! N$ h; C" }! DInvariance, 不变性# X% r* x9 O$ y5 s. T3 E
Inverse matrix, 逆矩阵
! v( J- n) J2 JInverse probability, 逆概率
( [; D5 c) Y" b. C; d3 D# CInverse sine transformation, 反正弦变换4 U/ ?" j8 t5 }. o# ^
Iteration, 迭代
; x+ k) U, x9 y _Jacobian determinant, 雅可比行列式
! A: }* C1 e: v# MJoint distribution function, 分布函数
7 X' ]+ a" `6 Q" GJoint probability, 联合概率
% X4 q* N2 w. b+ PJoint probability distribution, 联合概率分布
0 B+ y2 f: l6 {' O f3 aK means method, 逐步聚类法
/ U7 V/ I8 Z# N3 x6 VKaplan-Meier, 评估事件的时间长度 * m R6 M) A. } i$ B
Kaplan-Merier chart, Kaplan-Merier图1 i( C$ w, G$ b2 @
Kendall's rank correlation, Kendall等级相关
5 q' Z! _( g- M* g7 qKinetic, 动力学
& _* K& D* g' r6 RKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
& b- ^- M+ t4 M4 ^- @! cKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验: L ^) U) n# b \" I8 X
Kurtosis, 峰度: @$ e0 w8 ]5 [( J. ~ ]+ y0 T
Lack of fit, 失拟
0 S# E! k0 ] R4 I4 Y0 DLadder of powers, 幂阶梯+ p& c6 d2 j( Q9 [ Q2 C
Lag, 滞后
* t5 R+ b3 A# ?5 L5 ^# l! SLarge sample, 大样本
4 W) M& k8 n8 NLarge sample test, 大样本检验
3 a2 T& [ ^$ o. R, \9 A. oLatin square, 拉丁方% D- q, K2 q$ E/ q/ g
Latin square design, 拉丁方设计
4 m( H( U; C) s* G% _Leakage, 泄漏
3 t- Y. e2 o$ I# ?6 a( d0 JLeast favorable configuration, 最不利构形7 `/ i- a$ Y; ^8 p3 H& ~) U
Least favorable distribution, 最不利分布6 E# y3 @) E1 A2 N! R _9 S
Least significant difference, 最小显著差法4 |5 }7 z6 ?6 D9 @2 u) m K) O
Least square method, 最小二乘法
5 X# i$ k: ~7 T: p' j* B! m+ cLeast-absolute-residuals estimates, 最小绝对残差估计( D* E5 { _4 f) t2 }# y3 R/ E4 k6 K
Least-absolute-residuals fit, 最小绝对残差拟合
- I( O+ ^& S! j: z8 F+ oLeast-absolute-residuals line, 最小绝对残差线- ]; H8 E V9 ^! z
Legend, 图例% F6 s. D- f) s
L-estimator, L估计量
/ l0 [5 @$ W0 o$ V' ^5 J, A+ oL-estimator of location, 位置L估计量5 f; a- y) m! k- G
L-estimator of scale, 尺度L估计量! ]1 u# l; t$ x a6 [2 e, |
Level, 水平# Y( a$ W& I4 u+ t8 f
Life expectance, 预期期望寿命. W& {0 w, Q5 L7 Y/ {
Life table, 寿命表
. Q) \0 B! J; R# k/ {Life table method, 生命表法
$ A0 z0 b+ o5 w0 [Light-tailed distribution, 轻尾分布
: C) b0 e0 B3 l* t5 H( LLikelihood function, 似然函数
3 u0 D& C% u8 }2 [Likelihood ratio, 似然比& x" `; w: k! I9 x8 r8 }9 S
line graph, 线图
: b3 A m p. X6 m4 f# f! oLinear correlation, 直线相关- R$ L3 P0 j, ?+ j* e2 v7 @. _
Linear equation, 线性方程% U5 M, Y' x8 C: _" T3 a9 @/ H9 L
Linear programming, 线性规划3 A+ x4 W9 X7 o, d2 P+ v$ @) u
Linear regression, 直线回归/ f+ N8 f/ I* q) o! k7 N& w
Linear Regression, 线性回归
8 i: {* i" o& }Linear trend, 线性趋势
0 ~& o/ c9 G0 o* vLoading, 载荷 2 D' s* l3 o' a9 g3 E7 v1 N
Location and scale equivariance, 位置尺度同变性9 c9 J! M8 `" O0 ~2 Y5 f9 _. A1 P" B# y
Location equivariance, 位置同变性
! d1 c, V5 f4 A9 J/ vLocation invariance, 位置不变性
, P7 e( V0 f: d; SLocation scale family, 位置尺度族6 |$ k" A1 V/ {+ k
Log rank test, 时序检验
4 U1 Z+ |( v. p' m. fLogarithmic curve, 对数曲线
3 _% P& u) f7 Q9 S4 {7 T- t: L- ALogarithmic normal distribution, 对数正态分布2 w9 O2 Q0 g: `
Logarithmic scale, 对数尺度4 W! d4 t2 f/ m4 w" t8 {
Logarithmic transformation, 对数变换* \ H R& V: H+ C% G
Logic check, 逻辑检查
3 x( j9 Z( A) d! |7 w0 rLogistic distribution, 逻辑斯特分布
- ?- ~6 ?* t3 k, w: Q+ {Logit transformation, Logit转换
, t, y: W1 @3 q; FLOGLINEAR, 多维列联表通用模型
( v$ A0 r, n, ~; D2 \. `' HLognormal distribution, 对数正态分布# }# `( g C/ s: [5 D
Lost function, 损失函数 N/ B o% T6 G- \
Low correlation, 低度相关# Y0 A, d/ v7 O8 H2 D' C( A
Lower limit, 下限
: y2 [8 k, W8 Q- `6 U' C* ?Lowest-attained variance, 最小可达方差/ i: p* J; ~5 |& {" q9 X
LSD, 最小显著差法的简称
& M0 I5 w' P, K% h6 rLurking variable, 潜在变量
# U- \/ S9 s4 {+ U" _; UMain effect, 主效应
# j3 \" ]" U: p" {6 kMajor heading, 主辞标目; n. ?: y4 o* m$ Q D/ W* t, s
Marginal density function, 边缘密度函数# B7 S' {- d! K8 z5 B
Marginal probability, 边缘概率0 D' j0 K# A( Y& A) C( X
Marginal probability distribution, 边缘概率分布
- s) b+ N2 b$ a' F6 B' r/ WMatched data, 配对资料
8 L f/ g& n4 }- K: b1 wMatched distribution, 匹配过分布 B0 i$ B. M5 @1 i! b/ c9 T
Matching of distribution, 分布的匹配
$ x/ J4 n q$ BMatching of transformation, 变换的匹配
3 q( T! a! {% u. IMathematical expectation, 数学期望0 ?8 L4 Y; K/ b# Y
Mathematical model, 数学模型/ F! S+ r4 ~/ P) s& l) _
Maximum L-estimator, 极大极小L 估计量
. N' e! {8 w1 G: gMaximum likelihood method, 最大似然法
3 u* c7 _! C( Q' EMean, 均数
7 a! n- \0 Y& e, Q% c# xMean squares between groups, 组间均方
8 i1 a. ~: e9 a$ G5 tMean squares within group, 组内均方
; O. A, [# X Y- V# i- ]0 zMeans (Compare means), 均值-均值比较, F& u$ C. i7 t
Median, 中位数* L+ U @# [% o& o
Median effective dose, 半数效量
3 p# \* z) Y4 b& c' LMedian lethal dose, 半数致死量
7 b% i4 {7 x* L1 aMedian polish, 中位数平滑
0 @) M3 @( _3 qMedian test, 中位数检验
# J% [; P3 u' G6 T8 r& V) rMinimal sufficient statistic, 最小充分统计量 P$ r7 Z2 `7 V; A
Minimum distance estimation, 最小距离估计- x: a$ z q9 U5 [! \4 ^
Minimum effective dose, 最小有效量
; J0 [; _6 f5 v+ k) a ~Minimum lethal dose, 最小致死量* V# d1 G2 `) |# W* X. F6 J& S+ m
Minimum variance estimator, 最小方差估计量
' B$ d$ ], M8 C4 HMINITAB, 统计软件包& j2 w+ h+ C4 D5 k
Minor heading, 宾词标目* x8 }5 ~. ~. A& m
Missing data, 缺失值
* q, K4 Q4 u7 O+ i1 n" \Model specification, 模型的确定
* W) }/ Q c+ B/ vModeling Statistics , 模型统计; K4 L- q7 a& u& W# Q- U
Models for outliers, 离群值模型
0 h7 A4 M9 t0 d2 t5 Q9 wModifying the model, 模型的修正
! ~4 q; n. W7 c3 l4 n: xModulus of continuity, 连续性模- ~4 q" C5 H$ b" I' v
Morbidity, 发病率 9 e C( |* y/ T9 h0 X/ Q0 x
Most favorable configuration, 最有利构形1 R1 _) d) {# J; @+ I! b R9 `
Multidimensional Scaling (ASCAL), 多维尺度/多维标度: D2 y6 O% b$ W( b+ C
Multinomial Logistic Regression , 多项逻辑斯蒂回归1 U3 x, @0 }. Z/ @! w, b; J' o" \+ c
Multiple comparison, 多重比较! _5 A U4 u. n0 v) ?* Y
Multiple correlation , 复相关
; B9 \7 e- u& e6 {Multiple covariance, 多元协方差
( \. p7 f2 w1 g" @ @1 G$ `Multiple linear regression, 多元线性回归) D- T) u" V: O0 j
Multiple response , 多重选项
$ |9 M( N& J5 h% B! ^Multiple solutions, 多解
" ]# }) u" g7 o% fMultiplication theorem, 乘法定理% ]; S8 w4 {! A* L- i+ Z1 F2 ?+ u
Multiresponse, 多元响应, T7 A( \- e& X' S9 Y& G R
Multi-stage sampling, 多阶段抽样& m) X J1 p. Q, p
Multivariate T distribution, 多元T分布+ ]' }8 O( d. P
Mutual exclusive, 互不相容
9 C5 y/ C( g# U; }Mutual independence, 互相独立/ b; |. }: U }' H# ?# _7 a: m- z
Natural boundary, 自然边界2 t! \8 s* u2 Y' x$ u
Natural dead, 自然死亡
6 \& f( R* i) J/ y. pNatural zero, 自然零
1 B; L1 C9 g* s& CNegative correlation, 负相关
0 k4 ] B8 L, ]2 INegative linear correlation, 负线性相关
, _" Y3 H3 Q+ O. oNegatively skewed, 负偏4 g5 l- U4 y0 C7 [8 r" b
Newman-Keuls method, q检验
& m9 Q1 N& q* hNK method, q检验* F* d& J0 e; W A8 m
No statistical significance, 无统计意义
: [2 p7 Q5 Z% o& n$ ~" wNominal variable, 名义变量
' ^% W4 }) a5 T( T$ KNonconstancy of variability, 变异的非定常性) n. s# Q( z! T
Nonlinear regression, 非线性相关9 H& s% z! V5 b v; K0 Z8 F
Nonparametric statistics, 非参数统计* B% K) H) T/ M4 _5 D7 v* M
Nonparametric test, 非参数检验% C. j7 o$ c6 I: J+ c! d/ ?
Nonparametric tests, 非参数检验
$ ~; {) [# q6 H( }& }Normal deviate, 正态离差
/ K8 |3 p" o2 N; v1 Y$ Y* FNormal distribution, 正态分布
* a" e' ]8 \# g) l& ?/ V, `Normal equation, 正规方程组 M$ ~) L- }/ J1 I% ] P8 V
Normal ranges, 正常范围! V1 R4 `2 j0 M% k* P
Normal value, 正常值+ a) q; @# d# y5 A0 `' n
Nuisance parameter, 多余参数/讨厌参数' t7 D/ h9 @! C1 b1 ]9 I j0 ]
Null hypothesis, 无效假设 / L; f) e6 Z, a
Numerical variable, 数值变量' p5 {% E5 j& e2 l" b5 x
Objective function, 目标函数2 W8 S4 G9 B9 I8 o3 @ ^
Observation unit, 观察单位$ q) v; Y" |5 q7 X b
Observed value, 观察值 Z, [/ [! a, u" @6 ?
One sided test, 单侧检验# g! w/ B- O5 c! |5 y% Z0 N- ?& a7 Z
One-way analysis of variance, 单因素方差分析
. d p% b3 w5 y# {5 [" ROneway ANOVA , 单因素方差分析
8 W) o! s- [( [+ ]4 [( c* hOpen sequential trial, 开放型序贯设计
- A7 W$ ]$ y7 t0 UOptrim, 优切尾
& h1 k* d! {; K3 HOptrim efficiency, 优切尾效率
5 X5 F" P$ x9 O) d# W0 F3 ~Order statistics, 顺序统计量
& J6 Y% I- E' f: _5 _/ U. IOrdered categories, 有序分类
$ m1 ]2 Z6 r$ G6 l1 fOrdinal logistic regression , 序数逻辑斯蒂回归
; c$ M, Z. t4 W' C5 Q: \) OOrdinal variable, 有序变量) o" H9 V7 l Z( u& m8 f: R
Orthogonal basis, 正交基) H( [; d1 Y% [- q. @0 q
Orthogonal design, 正交试验设计
. ^$ h" x' O( q3 r+ B; I. [7 MOrthogonality conditions, 正交条件
5 {5 N& G( R ^6 |% j" F2 E' Q3 kORTHOPLAN, 正交设计 " ^( r+ v- V' S# M2 \5 i$ b. p* C
Outlier cutoffs, 离群值截断点; _- I4 L* l+ y, D+ b
Outliers, 极端值3 n# G3 B% E( g# b
OVERALS , 多组变量的非线性正规相关
4 I( f' N3 U/ l6 f3 Z; Q+ P/ @Overshoot, 迭代过度
! M( z6 S8 {( `; p' k" KPaired design, 配对设计1 K+ E$ X' g; K: Q
Paired sample, 配对样本
+ F! `; m- r8 Q) q4 VPairwise slopes, 成对斜率8 l5 Q- L# a2 J5 h5 R! N
Parabola, 抛物线1 D/ K% x8 J% m
Parallel tests, 平行试验
: g9 y7 d2 K7 S$ EParameter, 参数3 I# Z! Y/ r/ C' E) h; @* f% P
Parametric statistics, 参数统计: u* k6 i6 g+ ?% }8 C2 Z
Parametric test, 参数检验' M& a* e% K: B: w- {% s
Partial correlation, 偏相关
# K4 V/ l+ c! v4 E- }* K' RPartial regression, 偏回归
/ }$ y) o! S) C, b) r' H. h$ v. bPartial sorting, 偏排序0 C5 s* {% X( V' E, ?6 [
Partials residuals, 偏残差1 L+ Z" U L4 G, u( N1 q
Pattern, 模式
; k% q7 E2 E0 @1 D( B: [9 r; aPearson curves, 皮尔逊曲线
8 S& e5 ~7 z/ A& pPeeling, 退层
9 E+ j5 ^7 q; R5 z. L- g! x7 RPercent bar graph, 百分条形图# h+ h5 d( F# l7 @/ E, B L/ f. e
Percentage, 百分比
) z+ v( e. U, |4 z" P2 g1 t" X/ qPercentile, 百分位数
3 G- u. Q! p9 u( P* o; {Percentile curves, 百分位曲线2 G! C0 |4 L) o1 y4 [
Periodicity, 周期性- F/ Q' U4 Z" c( b. ?' a
Permutation, 排列+ i2 {! f" n6 Z7 ?6 m
P-estimator, P估计量
+ ` k2 y$ E" P7 ^0 WPie graph, 饼图- } x; D3 k8 |, i6 l4 D% |3 i7 \
Pitman estimator, 皮特曼估计量
* o5 W: @2 b0 L8 q1 F' J- F _, fPivot, 枢轴量
8 r' \+ I# d6 @, `5 q' W+ ?$ k& WPlanar, 平坦
* H/ ~+ K. x7 H. f) p" B- W& @7 APlanar assumption, 平面的假设
( b; L! d+ l" C, ^5 ` XPLANCARDS, 生成试验的计划卡
7 v' n9 p. u" @# U) {' ]Point estimation, 点估计
5 x. J$ b- l7 X- B% lPoisson distribution, 泊松分布9 ?) M( i# T x/ Q
Polishing, 平滑
+ r8 a e2 D9 o' E2 ePolled standard deviation, 合并标准差
# G5 R* h, V5 W" w, K; W6 WPolled variance, 合并方差
- V# Y/ H6 ]7 Z6 _7 LPolygon, 多边图
4 ]) q2 s6 o% ^, P& b! B( u; D% }Polynomial, 多项式
( w, ~3 b# c t* o2 c1 G8 {) OPolynomial curve, 多项式曲线
! b+ D: q! U' S" E' r- W5 I% h: Y) s# dPopulation, 总体
* F9 E+ P, P: h& l8 D; ^Population attributable risk, 人群归因危险度
: u' \$ H# W! X& rPositive correlation, 正相关
; v: e' C3 g) I1 ]: t: NPositively skewed, 正偏
7 D) D" [: V5 {5 TPosterior distribution, 后验分布
6 y& U5 y4 O: h- q5 zPower of a test, 检验效能
( t* O) z8 s' fPrecision, 精密度+ ^5 S* I5 r/ C9 l
Predicted value, 预测值. j" n, l1 b. j% F! m8 J+ k3 ~
Preliminary analysis, 预备性分析( G8 C# o3 L4 y9 a: u
Principal component analysis, 主成分分析
, x& W. `$ t, C1 ~9 [6 v/ uPrior distribution, 先验分布
& ]" ^# F' ^6 A# B/ ?Prior probability, 先验概率
+ G% _9 w% g- R9 [Probabilistic model, 概率模型
" m. p2 {3 P4 xprobability, 概率' V% J8 |0 o1 }- |0 t" }
Probability density, 概率密度+ ]+ \! |* _" `4 n2 c0 e
Product moment, 乘积矩/协方差! Q* Q( S! _0 _. ~, G
Profile trace, 截面迹图
4 l; Q& F% ]# b1 C& Q/ VProportion, 比/构成比
4 [7 X' V. z. S3 |. W1 a4 h# SProportion allocation in stratified random sampling, 按比例分层随机抽样
' l m2 X; x" f# I% b" QProportionate, 成比例6 J6 g1 {3 J7 D* |
Proportionate sub-class numbers, 成比例次级组含量
4 f* @+ a& V& w* IProspective study, 前瞻性调查% p/ w3 w, i4 C5 d7 T
Proximities, 亲近性
4 S% K0 [% j) ^" z6 ]% y' R# UPseudo F test, 近似F检验- y; Y# ]% ]! Z( I# T
Pseudo model, 近似模型/ B# _- E1 R& L9 Y6 [/ W9 f. D# d1 t
Pseudosigma, 伪标准差
) X# T# r- t4 w! y3 l9 SPurposive sampling, 有目的抽样
0 r- ~& N% D* y8 U2 BQR decomposition, QR分解9 X5 Z- d6 Q6 o$ u- G8 t
Quadratic approximation, 二次近似9 ]0 X1 @. \- t, n. u
Qualitative classification, 属性分类
& W8 O! P# ^* c1 T* V' Z. y9 oQualitative method, 定性方法/ T& g2 q4 y9 T5 @2 K
Quantile-quantile plot, 分位数-分位数图/Q-Q图) u( a& {3 H* B6 [" v% o4 y
Quantitative analysis, 定量分析
- J% [0 m, \1 K1 F. Z6 M; UQuartile, 四分位数
+ s& p/ J+ j& x$ U+ X! L! WQuick Cluster, 快速聚类
' I$ T1 e" L( H' j3 k$ q$ iRadix sort, 基数排序. j- k* L- y6 Z8 _6 _" [
Random allocation, 随机化分组5 C @$ R5 e, j' Z T/ m( H2 x
Random blocks design, 随机区组设计. m1 ~; f8 L* n4 s
Random event, 随机事件
4 g! t! t; F4 X1 K: s3 @Randomization, 随机化
m; b4 W; t* ~; Q" u% {. ORange, 极差/全距
8 z3 o. B" v. }) p" u' Z1 gRank correlation, 等级相关" z8 w4 C; h! n" e
Rank sum test, 秩和检验% b; J# {; C& E) l' D9 ?
Rank test, 秩检验
; c$ q6 C4 h3 B4 j' yRanked data, 等级资料/ e" Y _; U! o
Rate, 比率
- o% X3 c( d+ ORatio, 比例
2 e# @( ^0 V4 z4 j" a2 ZRaw data, 原始资料
4 m) H6 _ s1 o* gRaw residual, 原始残差
8 _# y0 t- T- t/ w* c; }Rayleigh's test, 雷氏检验# u3 n5 e! T/ B1 ?
Rayleigh's Z, 雷氏Z值
O/ C( x0 ]) m* v. H1 jReciprocal, 倒数: y5 y5 s3 B. n7 O' i
Reciprocal transformation, 倒数变换; Y$ m0 M; `3 O9 w# }+ H8 [
Recording, 记录5 [/ i0 T" `/ s. e; B" d
Redescending estimators, 回降估计量
5 D9 u+ U9 n/ b# n: BReducing dimensions, 降维
1 ?3 \# J! f' b& j& d3 |% v' h$ ERe-expression, 重新表达
& J. F- P8 m( o6 ^2 GReference set, 标准组
0 Y) t/ s7 [$ j) HRegion of acceptance, 接受域! j. h- c c: g! c/ ~
Regression coefficient, 回归系数9 N9 U" s$ {& k. F) J6 _
Regression sum of square, 回归平方和$ I! ?; @0 _3 r6 T
Rejection point, 拒绝点8 q* I) e* R6 Y: G
Relative dispersion, 相对离散度1 ] ~% w( ?- n% T, f/ Q
Relative number, 相对数
5 }1 u$ x5 x# o$ G- s' cReliability, 可靠性! |5 I& |, r) r) t2 _8 B) p! K: W
Reparametrization, 重新设置参数) O2 \( ?7 X# W* E
Replication, 重复, X4 Q9 j- i3 V+ v* o7 E- X9 V
Report Summaries, 报告摘要- G+ }% i$ ~0 N+ \0 s, U
Residual sum of square, 剩余平方和
& N- `6 m- g0 S/ g* C- T; DResistance, 耐抗性( ]9 s+ P- U+ }3 A8 @
Resistant line, 耐抗线. e, G5 M; r( W3 b! F1 P; A
Resistant technique, 耐抗技术" y$ T0 G: a$ a, v
R-estimator of location, 位置R估计量
0 J5 _, o1 [- u, m3 g7 K, D" W/ \1 z( zR-estimator of scale, 尺度R估计量 r; ]# n1 k2 U+ n7 N8 F0 g
Retrospective study, 回顾性调查0 R4 Z& Z9 U; S, a& S& g+ t
Ridge trace, 岭迹3 z5 v% D$ z4 V. n) h" j6 h
Ridit analysis, Ridit分析; g7 Z$ b! R) F8 O6 |" P7 _0 a
Rotation, 旋转
% l) }. a8 Q" j+ x9 cRounding, 舍入
" Z1 P% N2 \) J; a0 P# ORow, 行
/ U% Q& ?, a3 x6 yRow effects, 行效应
( g2 c" z& \7 h, qRow factor, 行因素
' j3 g, z/ c8 o& RRXC table, RXC表. [9 v% o! D+ N0 D) E, e6 I
Sample, 样本
& w3 n+ X# j$ ESample regression coefficient, 样本回归系数 _9 Q; s8 T/ [( W
Sample size, 样本量" D, r( \' ]% Q) F7 Z/ g
Sample standard deviation, 样本标准差1 X5 K2 \) j$ E' H: F, V9 e
Sampling error, 抽样误差2 ^6 r* h1 |" f- v8 R9 e! U& S
SAS(Statistical analysis system ), SAS统计软件包
* ?+ o& M, [! Q: m) ~" GScale, 尺度/量表1 P P! _3 S: u* M# e1 W i
Scatter diagram, 散点图
6 o% u h- L* L3 Q, bSchematic plot, 示意图/简图1 i8 ]2 H8 s+ z5 S! L
Score test, 计分检验
8 I8 I4 k* G+ u$ oScreening, 筛检8 W: R1 O5 u! B9 @# P
SEASON, 季节分析
1 H+ H! \, w/ u' R3 MSecond derivative, 二阶导数; N$ m* J8 Y: ?4 V( [
Second principal component, 第二主成分
. x3 h: d# b e: }9 U1 ~SEM (Structural equation modeling), 结构化方程模型
+ L, t- ^; g/ t: n9 ^/ |# qSemi-logarithmic graph, 半对数图
! F( m: p* s# Q# c3 v: zSemi-logarithmic paper, 半对数格纸
% F" o* v: k5 \" W; l) [8 TSensitivity curve, 敏感度曲线0 Z! B! {% U5 c6 T+ N3 P. h
Sequential analysis, 贯序分析: Z( Q* v9 r- ^ [. t' H" N- }/ n
Sequential data set, 顺序数据集2 [' [' Q/ L0 `/ n- w
Sequential design, 贯序设计
/ {: x' p' H5 A6 D7 {Sequential method, 贯序法
5 P: e) L5 V$ WSequential test, 贯序检验法
4 z! t# e5 |. Y W$ MSerial tests, 系列试验
. r+ P$ V+ c; yShort-cut method, 简捷法
- `- g% R! ^. n8 DSigmoid curve, S形曲线
! N- u$ d( u7 ]) F, R# B0 nSign function, 正负号函数
4 c2 z9 D+ X. t4 l+ M, j5 a1 ISign test, 符号检验. b* ?$ c) K Q+ b3 F
Signed rank, 符号秩
. |7 v- r2 L$ Q2 V3 y# }* s Z; FSignificance test, 显著性检验/ j4 [# c5 W: ^9 y$ k# G+ @+ b: V1 D
Significant figure, 有效数字 l9 |: H: y/ B$ B' I
Simple cluster sampling, 简单整群抽样
/ E, g! h- p+ C; nSimple correlation, 简单相关
8 g5 Y1 P) y6 L2 `9 J% wSimple random sampling, 简单随机抽样8 @ a$ N$ W5 P: w' e
Simple regression, 简单回归; K/ H9 h, z* }, x, N! |
simple table, 简单表% H6 l o! X" \* B( N& v
Sine estimator, 正弦估计量
. X" {- a0 R' ]/ BSingle-valued estimate, 单值估计1 [) k0 _# @. `" m7 I; k! h
Singular matrix, 奇异矩阵
2 p( N/ O* ?+ U& gSkewed distribution, 偏斜分布! `* `& f4 Y/ v$ H9 u) Y7 ~
Skewness, 偏度
4 i. M% P0 t: s+ y6 T9 W$ O" KSlash distribution, 斜线分布
" E3 m1 p: q9 YSlope, 斜率2 L }; o8 ^& S5 ^" Y' {
Smirnov test, 斯米尔诺夫检验3 w" E% S3 m2 P
Source of variation, 变异来源* s& n* U" @0 D0 Y
Spearman rank correlation, 斯皮尔曼等级相关
* V$ R% o& g, n7 _9 Q* fSpecific factor, 特殊因子
5 O5 v; U9 \3 H( ]" @Specific factor variance, 特殊因子方差
. w7 @5 z( z2 j0 q( n9 ~3 KSpectra , 频谱
9 `% j% k" W1 e. J) NSpherical distribution, 球型正态分布
0 z( w9 [' G/ j' aSpread, 展布8 ] x) d1 R& D, O8 p, r
SPSS(Statistical package for the social science), SPSS统计软件包
4 ^1 X8 ~: H* n8 w5 jSpurious correlation, 假性相关
* y n* Y( _: ]: p' iSquare root transformation, 平方根变换
" m8 g1 A- L. ZStabilizing variance, 稳定方差
( u4 ~: a- S$ GStandard deviation, 标准差. x$ F4 @! e: W% _5 [) r
Standard error, 标准误
s' z" |; ^" W0 t4 X5 GStandard error of difference, 差别的标准误
8 ]7 k3 O1 G3 V+ YStandard error of estimate, 标准估计误差( j, Z; B5 X+ S! j
Standard error of rate, 率的标准误
# @* t" x4 y/ ^/ JStandard normal distribution, 标准正态分布
, B, S: N" T+ K* U; ZStandardization, 标准化; G( u( S' n6 w# t/ l, y4 B
Starting value, 起始值
! @, a: J. c# eStatistic, 统计量( Z! U: i+ E+ Z+ n) _ j
Statistical control, 统计控制. H2 k* h6 p, I6 Q9 @# \5 F1 W
Statistical graph, 统计图: Z+ S. b/ r# f# v1 S Q
Statistical inference, 统计推断/ ]/ k ~$ \( C6 g! `/ i
Statistical table, 统计表) N) N* X' g* f" Y
Steepest descent, 最速下降法
7 y( r2 |( H8 w! h" Z) _! DStem and leaf display, 茎叶图& B: c8 k5 l+ b4 a( k/ y
Step factor, 步长因子% H" c+ r) x. C
Stepwise regression, 逐步回归
/ b/ K8 `/ }/ N0 T" YStorage, 存
$ R' _ c2 B; @" [2 eStrata, 层(复数)
2 z* g7 b6 M" O' K4 k8 _/ {! I! tStratified sampling, 分层抽样
, R1 i, K* J2 e# DStratified sampling, 分层抽样
7 e& z+ J* j* ?% i5 R9 L8 |% `- C8 SStrength, 强度8 D1 k. ]2 Y6 k. d' l( f, ?
Stringency, 严密性2 [8 u/ F7 ?% C# [$ k: m h. Y
Structural relationship, 结构关系
) o% O9 a4 |, i: bStudentized residual, 学生化残差/t化残差& P1 v8 I1 v4 R, P0 ~
Sub-class numbers, 次级组含量5 ]- ^* J5 V2 N7 S I& K
Subdividing, 分割
p( Q# C( a3 |Sufficient statistic, 充分统计量( [- G4 r: T0 E* O L# A
Sum of products, 积和
# h4 Z5 S) i* d" x. o) w6 x4 QSum of squares, 离差平方和
7 }# _+ k6 Z0 z* K6 s7 PSum of squares about regression, 回归平方和/ c r8 n0 w5 N
Sum of squares between groups, 组间平方和8 i( @" T4 z" C ~4 }% E/ l
Sum of squares of partial regression, 偏回归平方和
' T! u4 D. _, y$ p: N7 G% N& s$ ^Sure event, 必然事件7 W$ P& Z% i1 `6 ?) \
Survey, 调查9 Z+ \" v. l% a+ l! W9 r2 t# u1 f
Survival, 生存分析
# y* _, @ j7 g: F( K: ISurvival rate, 生存率
; ]1 P" j9 u0 \& j" Z9 @Suspended root gram, 悬吊根图8 t8 P5 j3 J `+ P
Symmetry, 对称: G# r5 @) ^% d: B+ v ~
Systematic error, 系统误差
; K0 Y( d- a. x. {# v5 N) uSystematic sampling, 系统抽样* W7 z$ f; u! ]( `8 S9 z) N( q
Tags, 标签
: F9 F* V5 r- D3 dTail area, 尾部面积; S v! V" _* ~& J
Tail length, 尾长3 I. f; d* h# n1 z/ }
Tail weight, 尾重; E" X' P8 I) G/ Y" u/ _% J
Tangent line, 切线( v) P6 q ~( @8 E u8 n
Target distribution, 目标分布* k& V, `" ]6 ~& J6 N+ G
Taylor series, 泰勒级数
" U- k/ n% D# e8 OTendency of dispersion, 离散趋势
' J4 s4 `" X% l% X0 ^Testing of hypotheses, 假设检验
9 x: o# m& @' s; I% v8 XTheoretical frequency, 理论频数
8 a( o& x6 G) B# \4 ITime series, 时间序列 q% F! X8 c: g' S- R6 X
Tolerance interval, 容忍区间0 M, j# |+ y! e" }# m$ k
Tolerance lower limit, 容忍下限: W. H3 {( r! A( p( { Z
Tolerance upper limit, 容忍上限, `1 |/ y* [/ @( C* P0 l2 X3 d
Torsion, 扰率
& ^9 ~, F8 T; @" d0 x9 F1 j+ @0 NTotal sum of square, 总平方和+ ^( {4 _* p; ^ F" e1 k& ?+ H
Total variation, 总变异
6 c9 M Q. P/ O0 b" v( UTransformation, 转换
! e! m* g5 O- @Treatment, 处理
/ x% X' [, H6 K! cTrend, 趋势' k* c0 } f! R! k6 q& m' j5 O
Trend of percentage, 百分比趋势
" n/ _$ ^4 v8 ~4 X/ BTrial, 试验0 S; U+ N( S8 [' a j
Trial and error method, 试错法
2 O% T u7 h) q% |' J* a FTuning constant, 细调常数+ }' s0 h5 m8 d( C6 @$ _5 K
Two sided test, 双向检验1 u( s. m, Z8 S" ^# n O5 @: \
Two-stage least squares, 二阶最小平方7 Q- Q R2 w V/ d; u0 B
Two-stage sampling, 二阶段抽样1 ^4 ]- p4 L. r: U+ A$ s6 C
Two-tailed test, 双侧检验
$ _$ v( q9 ?0 J. K, b$ ?Two-way analysis of variance, 双因素方差分析
8 \! |/ q& P( n$ |- n* t. I4 T3 ^6 LTwo-way table, 双向表
- l8 t; D. a) b5 \6 rType I error, 一类错误/α错误9 n) q, b: H- I w( I4 d
Type II error, 二类错误/β错误/ v! n" N& `- y! a! I
UMVU, 方差一致最小无偏估计简称
% o: w3 @- N5 v( s" VUnbiased estimate, 无偏估计
: j; H+ v2 l7 }. FUnconstrained nonlinear regression , 无约束非线性回归7 Q9 P6 @+ U9 v% L2 ^
Unequal subclass number, 不等次级组含量 X8 H* I" P! q" N/ ~
Ungrouped data, 不分组资料
- [. r3 d, d; {! pUniform coordinate, 均匀坐标4 Z/ ^! L% [. L- `% Q
Uniform distribution, 均匀分布
8 q" {$ A# b5 p) T" d& P7 YUniformly minimum variance unbiased estimate, 方差一致最小无偏估计5 H `2 J! K+ t5 c# n0 x
Unit, 单元
9 L" y. w; W* S: l0 u- L6 MUnordered categories, 无序分类9 @! K s7 ^: x( S+ { l# h9 ?
Upper limit, 上限1 ?0 r2 g: U: A9 S7 r
Upward rank, 升秩
# A: v8 x% A. c: q) l' m. dVague concept, 模糊概念3 K4 P+ ?8 M- L0 d
Validity, 有效性
( @: \+ V( B( F: e! u8 EVARCOMP (Variance component estimation), 方差元素估计
5 x4 `/ N+ U9 R" s! OVariability, 变异性
( |/ R+ p- {# K2 s7 U# @Variable, 变量' l7 S) n6 t# J5 \7 P1 U C* O
Variance, 方差
8 I: P& u$ W3 Y4 @1 bVariation, 变异
, R9 p' l' N! yVarimax orthogonal rotation, 方差最大正交旋转# j2 y* c7 V g2 H
Volume of distribution, 容积+ d7 R; M7 E6 [% {/ E
W test, W检验# v- {' {, p- {/ P: c
Weibull distribution, 威布尔分布& ?/ e* Y; e! _8 `! x3 d6 X6 E
Weight, 权数8 W# z8 J7 s6 K
Weighted Chi-square test, 加权卡方检验/Cochran检验( |1 ^8 I" x3 m
Weighted linear regression method, 加权直线回归
6 J- ` g: P: l; V2 k' N3 w( DWeighted mean, 加权平均数: A' _* p( y! I4 K2 l
Weighted mean square, 加权平均方差2 c& b' U2 R1 v- x1 I
Weighted sum of square, 加权平方和; @ i3 d, z9 u/ d1 y0 F
Weighting coefficient, 权重系数6 {, y" t2 Z- L, r1 q7 B- n
Weighting method, 加权法 + Y- X/ ]/ ^. P( r- R# Y( L; v
W-estimation, W估计量) l0 t+ P* u4 a# M6 p* ^6 y* t
W-estimation of location, 位置W估计量- u# V5 C* T$ j7 h9 B3 k
Width, 宽度" V, Q% Y8 N5 ~! i9 Q
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验, a8 G7 H9 ^# E# g
Wild point, 野点/狂点
" _1 e% u& }3 K$ qWild value, 野值/狂值+ l& x5 X( Q* i
Winsorized mean, 缩尾均值
- A/ B( }2 A3 ~Withdraw, 失访 1 _8 l" ]; p7 k& O6 r
Youden's index, 尤登指数
0 ^8 A6 [" a/ X8 [" t8 z( c7 e/ z' aZ test, Z检验- H- |" q1 u. v9 t! A
Zero correlation, 零相关- @% {) y) `" ]& }
Z-transformation, Z变换 |
本帖子中包含更多资源
您需要 登录 才可以下载或查看,没有账号?注册会员
x
|